Helper function for ggstatsplot::ggcorrmat to apply this
function across multiple levels of a given factor and combining the
resulting plots using ggstatsplot::combine_plots.
grouped_ggcorrmat(
data,
cor.vars = NULL,
cor.vars.names = NULL,
grouping.var,
title.prefix = NULL,
output = "plot",
...,
plotgrid.args = list(),
title.text = NULL,
title.args = list(size = 16, fontface = "bold"),
caption.text = NULL,
caption.args = list(size = 10),
sub.text = NULL,
sub.args = list(size = 12)
)Dataframe from which variables specified are preferentially to be taken.
List of variables for which the correlation matrix is to be
computed and visualized. If NULL (default), all numeric variables from
data will be used.
Optional list of names to be used for cor.vars. The
names should be entered in the same order.
A single grouping variable (can be entered either as a
bare name x or as a string "x").
Character string specifying the prefix text for the fixed
plot title (name of each factor level) (Default: NULL). If NULL, the
variable name entered for grouping.var will be used.
Character that decides expected output from this
function: "plot" (for visualization matrix) or "correlations" (or
"corr" or "r"; for correlation matrix) or "p-values" (or "p.values"
or "p"; for a matrix of p-values) or "ci" (for a tibble with
confidence intervals for unique correlation pairs; not available for robust
correlation) or "n" (or "sample.size" for a tibble with sample sizes
for each correlation pair).
Arguments passed on to ggcorrmat
matrix.typeCharacter, "full" (default), "upper" or "lower",
display full matrix, lower triangular or upper triangular matrix.
typeA character string indicating which correlation
coefficient is to be computed ("pearson" (default) or "kendall" or
"spearman"). "robust" can also be entered but only if output argument
is set to either "correlations" or "p-values". The robust correlation
used is percentage bend correlation (see ?WRS2::pball). Abbreviations
will also work: "p" (for parametric/Pearson's r), "np"
(nonparametric/Spearman's rho), "r" (robust).
betaA numeric bending constant for percentage bend robust correlation
coefficient (Default: 0.1).
sig.levelSignificance level (Default: 0.05). If the p-value in
p-value matrix is bigger than sig.level, then the corresponding
correlation coefficient is regarded as insignificant and flagged as such in
the plot. This argument is relevant only when output = "plot".
p.adjust.methodWhat adjustment for multiple tests should be used?
("holm", "hochberg", "hommel", "bonferroni", "BH", "BY",
"fdr", "none"). See stats::p.adjust for details about why to use
"holm" rather than "bonferroni"). Default is "none". If adjusted
p-values are displayed in the visualization of correlation matrix, the
adjusted p-values will be used for the upper triangle, while
unadjusted p-values will be used for the lower triangle of the
matrix.
colorsA vector of 3 colors for low, mid, and high correlation values.
If set to NULL, manual specification of colors will be turned off and 3
colors from the specified palette from package will be selected.
subtitleThe text for the plot subtitle.
captionThe text for the plot caption. If NULL, a default caption
will be shown.
caption.defaultLogical that decides whether the default caption
should be shown (default: TRUE).
pchDecides the glyphs (read point shapes) to be used for
insignificant correlation coefficients (only valid when insig = "pch").
Default value is pch = 4.
ggcorrplot.argsA list of additional (mostly aesthetic) arguments that
will be passed to ggcorrplot::ggcorrplot function. The list should avoid
any of the following arguments since they are already being used: corr,
method, p.mat, sig.level, ggtheme, colors, matrix.type, lab,
pch, legend.title, digits.
kDecides the number of decimal digits to be displayed
(Default: 2).
ggthemeA function, ggplot2 theme name. Default value is
ggplot2::theme_bw(). Any of the ggplot2 themes, or themes from
extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(),
hrbrthemes::theme_ipsum_ps(), etc.).
ggstatsplot.layerLogical that decides whether theme_ggstatsplot
theme elements are to be displayed along with the selected ggtheme
(Default: TRUE). theme_ggstatsplot is an opinionated theme layer that
override some aspects of the selected ggtheme.
methodSmoothing method (function) to use, accepts either
NULL or a character vector, e.g. "lm", "glm", "gam", "loess"
or a function, e.g. MASS::rlm or mgcv::gam, stats::lm, or stats::loess.
"auto" is also accepted for backwards compatibility. It is equivalent to
NULL.
For method = NULL the smoothing method is chosen based on the
size of the largest group (across all panels). stats::loess() is
used for less than 1,000 observations; otherwise mgcv::gam() is
used with formula = y ~ s(x, bs = "cs") with method = "REML". Somewhat anecdotally,
loess gives a better appearance, but is \(O(N^{2})\) in memory,
so does not work for larger datasets.
If you have fewer than 1,000 observations but want to use the same gam()
model that method = NULL would use, then set
method = "gam", formula = y ~ s(x, bs = "cs").
conf.levelScalar between 0 and 1. If unspecified, the defaults return
95% lower and upper confidence intervals (0.95).
messagesDecides whether messages references, notes, and warnings are
to be displayed (Default: TRUE).
packageName of package from which the palette is desired as string or symbol.
paletteName of palette as string or symbol.
directionEither 1 or -1. If -1 the palette will be reversed.
A list of additional arguments to cowplot::plot_grid.
String or plotmath expression to be drawn as title for the combined plot.
A list of additional arguments
provided to title, caption and sub, resp.
String or plotmath expression to be drawn as the caption for the combined plot.
A list of additional arguments
provided to title, caption and sub, resp.
The label with which the combined plot should be annotated. Can be a plotmath expression.
A list of additional arguments
provided to title, caption and sub, resp.
Correlation matrix plot or correlation coefficient matrix or matrix of p-values.
https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggcorrmat.html
# NOT RUN {
# for reproducibility
set.seed(123)
# for plot
# (without specifying needed variables; all numeric variables will be used)
ggstatsplot::grouped_ggcorrmat(
data = ggplot2::msleep,
grouping.var = vore
)
# for getting plot
ggstatsplot::grouped_ggcorrmat(
data = ggplot2::msleep,
grouping.var = vore,
cor.vars = sleep_total:bodywt,
corr.method = "r",
p.adjust.method = "holm",
colors = NULL,
package = "wesanderson",
palette = "BottleRocket2",
plotgrid.args = list(nrow = 2)
)
# for getting correlations
ggstatsplot::grouped_ggcorrmat(
data = ggplot2::msleep,
grouping.var = vore,
cor.vars = sleep_total:bodywt,
output = "correlations"
)
# }
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